Using ecocloud requires some basic understanding of either R or Python, but even without this ecocloud provides a great platform to learn, and you can start using it. 

Steps to use the ecocloud Platform

1. Log in

2. Start a server

3. Add data to your workspace

4. Add code and analyses

5. Share your analyses

6. Save your analyses

7. Log off

Steps in more detail

1. Log in

If you are associated with an Australian university or institution linked to the Australian Access Federation (AAF), you can log into ecocloud using your institution credentials. Otherwise, you can create your own login account.

1.1 Using your university/institute log in

• Open your web browser
• Go to https://app.ecocloud.org.au/ 
• Click Sign In
• Select the Sign in with AAF button
• Search for your organisation and follow the prompts to log in

1.2 Using an alternative login

• Open your web browser
• Go to https://app.ecocloud.org.au/ 
• Click Sign In
• Select the Sign in using another ID 
• Enter your credentials and follow the prompts to log in

2. Start a server

Once you are logged in you will be on your Dashboard page. From this page you can launch a server to begin your session. 

To launch your notebook server click on the orange button labelled Launch notebook server.

2.1 Choose your preferred code language

Now you will be prompted to select your preferred code language and interface from either Python (SciPy Notebook) or R (RStudio Notebook).

Once your server is running you are now ready to open it, and beginning you analysis. You can open it by selecting the green Open button. When you click on this, it will open a JuypterLab in a new tab. 

3. Add data to your workspace

In this example, we have launched an RStudio Notebook. Within the server you have two panels; the panel on the left hand side allows you access to your files, folders, and links with Google Drive and GitHub. The panel on the right hand side when you first open it up will be your launcher.

 3.1 Set the directory

The first most important thing is that you enter the folder titled 'workspace' (circled in red above). Any data, work or analyses you do outside of your workspace will not be saved at the end of your session. This is critical.

Here are a few ways to make sure you are in your workspace directory:

• In RStudio: setwd("/home/jovyan/workspace")
• In R Notebook: double click on the 'workspace' folder
• In Python: os.chdir(/home/jovyan/workspace")
• In the Terminal: cd workspace

3.2 Choose your preferred interface

Once you are in your workspace folder, you can use the Launcher panel on the right to select either the R Notebook, RStudio or RShiny, depending on your preference. We have a short explainer article about the difference between these, and how to get started using them here. You are not limited to just using one of these, instead, you can create multiple R Notebooks. To an additional Notebook, click File > New > Notebook in the top left hand side of the JupyterLab.

3.3 Upload your data

To add data, you first upload it to the workspace by selecting the 'up-arrow' button in the left hand panel:

Once uploaded, the data will appear in your workspace folder. 

3.4 Import freely available datasets

We are still writing the support for this, check back here soon. 

4. Add code and analyses

The code you add and analyses you do is entirely up to you and is dependent on your data and your research questions. 

4.1 Add your own code

If you already know what analyses you would like to do, you can start straight away. Because this analysis will be running on a cloud platform, you will be able to leave the tab open and continue other tasks, without slowing your computer down.

4.2 Access freely available code

We are still writing the support for this, check back here soon.

5. Share your analyses

We are still writing the support for this, check back here soon. 

6. Save your analyses

Depending on what interface you are using (RStudio, R Notebook, Python), saving you work differs slightly, but ultimately you can save everything by selecting File > Save within each interface. Just remember to check that you are saving the session in your workspace folder - if it is in any other folder it will not be available when you log back in. 

7. Log off

Once you have finished in your session and everything is saved, you can close your tab. Before closing all your browsers, it is important that you terminate the server. This can be done from your Dashboard where you originally launched the server, by clicking on the red terminate button.